Methods and systems for identification and visualization of bias and fairness for machine learning models

A computer system comprising:

• a server having one or more processors configured to:
• receive a feature of a plurality of features used by a model to generate output, wherein the feature comprises a plurality of categories, and the output comprises a plurality of types;
• identify a metric used to evaluate a performance of the model and a threshold for the metric;
• determine a value for the metric for a category of the plurality of categories of the feature based on a comparison of a first number of values of a first type of the plurality of types output by the model for the category with a second number of values of the first type output by the model for the second category;
• and
• generate a notification indicating the performance of the model responsive to a comparison of the value for the metric with the threshold for the metric.

A computer system comprising:

• a server comprising a processor and a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to perform operations comprising:
• receiving a feature of a plurality of features used by a model to generate output, wherein the feature comprises a plurality of categories, and the output comprises a plurality of types;
• identifying a metric used to evaluate a performance of the model and a threshold for the metric;
• determining a value for the metric for a category of the plurality of categories of the feature based on a comparison of a first number of values of a first type of the plurality of types output by the model for the category with a second number of values of the first type output by the model for the second category;
• and
• generating a notification indicating the performance of the model responsive to a comparison of the value for the metric with the threshold for the metric.